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Both univariate descriptive statistics and multivariate statistical techniques were employed for the analysis of data.
Four multivariate statistical techniques were used for this analysis.
Many of the data from these investigations are analyzed using multivariate statistical techniques such as parallel independent component analysis.
This paper describes fundamentals and applications of multivariate statistical techniques for the optimization of chromatographic systems.
We used cognitive task analysis and multivariate statistical techniques to characterize the relationships between performance metrics.
Next, three classification models were calibrated in a training area using different multivariate statistical techniques.
Several univariate and multivariate statistical techniques were employed for data treatment.
What it is: A variety of multivariate statistical techniques (factoring, pca, ica, k-means) that empirically form groups with common traits (clusters) that had not been previously defined.
A number of multivariate statistical techniques were used to attempt to investigate the perceived dimensional structure of the different therapies.
Responses were analysed with respect to functional trait groups in the associated polychaete assemblage using uni- and multivariate statistical techniques.
Particularly, the combination of fuzzy clustering with multivariate statistical techniques for Process Supervision Strategies (PSS) has been studied.
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